Academy of Management Perspectives
Behind the Scenes: Intermediary organizations that
facilitate
science commercialization through entrepreneurship
Journal:
Manuscript ID
Document Type:
Keywords:
Academy of Management Perspectives
AMP-2016-0133.R3
Symposium
Entrepreneurship (General) < Entrepreneurship < Topic Areas, Venture
capital < Entrepreneurship < Topic Areas, Innovation Processes <
Technology and Innovation Management < Topic Areas
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Academy of Management Perspectives
Behind the Scenes: Intermediary organizations that facilitate
science commercialization through entrepreneurship
Paige Clayton
University of North Carolina
clayton3@live.unc.edu
Maryann Feldman
University of North Carolina
maryann.feldman@unc.edu
Nichola Lowe
University of North Carolina
nlowe@email.unc.edu
Acknowledgements: The National Science Foundation and the Ewing Marion Kauffman
Foundation provided funding.
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Abstract: Lacking resources to commercialize science, entrepreneurs rely on intermediary
organizations often within their local ecosystems. This paper seeks to improve our
understanding of how intermediaries operate to advance the commercialization of science
by providing a set of specialized services. We review five intermediaries commonly
mentioned in the ecosystem literature: university technology transfer offices; professional
service firms; networking, connecting and assisting organizations; incubators, accelerators,
and coworking spaces; and financing entities—including venture capital, public financing,
angel financing and crowdsourcing. Specifically, we explore how these various
intermediaries function and provide complementary and related services in support of
scientific commercialization through entrepreneurship. After defining intermediation, we
review the literature on each organization type, providing a definition and considering the
contribution of the intermediary and the related policy implications. Each section
concludes with suggestions for additional research.
Keywords: intermediaries; science commercialization; scientific entrepreneurship;
entrepreneurial ecosystem; entrepreneurial support organization.
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I.
Introduction
A successful theater performance requires a large support cast working behind the
scenes, without which the show would not go on. Just as the audience focuses their
attention on the dramatic action happening on stage, the commercialization of science
tends to orient its gaze toward the innovative technology and its enabling star, the
entrepreneur. But as with theater, diverse entities work behind the scenes to support the
necessary processes of founding, managing and scaling a new scientific venture. In the
commercialization of science, the least visible players are intermediary organizations —
entities that operate in the void between the scientific discovery and the ultimate
realization of value from commercialization, providing specialized services and access to
equipment and resources beyond the reach of startup firms. Although these support
organizations have a long history in helping disseminate information important to
technology innovation, they are often treated as tangential to the study of science-based
entrepreneurship (Howells, 2006). Yet varying access to these background supports can
have a profound effect on entrepreneurial performance, as well as help sustain innovative
activities within a regional economy (Cooke, Uranga, & Etxebarria, 1997).
Academic interest in entrepreneurial ecosystems creates an opportunity to shine
the spotlight on these behind the scenes organizations. By definition, ecosystems are “a set
of interconnected entrepreneurial actors, institutions, entrepreneurial organizations and
entrepreneurial processes which formally and informally coalesce to connect, mediate and
govern the performance within the entrepreneurial environment,” (Mason & Brown, 2014,
pp. 5). Thus, the nascent ecosystem literature makes room for a variety of innovation-
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supporting intermediaries, including: nonprofit, private, and public organizations, as well
as universities, incubators, entrepreneurial support organizations, professional service
providers and venture capitalists (Isenberg, 2011; Mason & Brown, 2014; Auerswald,
2015; Bell-Masterson & Stangler, 2015; Mack & Mayer, 2015; Stam, 2015). The ecosystem
model also suggests an organic and fluid relationship between intermediaries that coevolve
in a place. However, in order to fully appreciate the synergistic effects of this relational
dynamic, we first need to recognize the contribution each intermediary makes to this
science commercialization ecosystem. While each type of intermediary offers the potential
to bring unique—yet complementary—services and supports to a regional ecosystem,
there is also the potential for multiple intermediaries to coordinate, and even duplicate,
efforts in order to address persistent innovation challenges or gaps.
The first objective of this paper is to improve our understanding of intermediaries
in the commercialization of science. We limit our review to five intermediaries that support
science commercialization commonly mentioned in the ecosystem literature: university
technology transfer offices; professional service firms; networking, connecting and
assisting organizations; incubators, accelerators, and coworking spaces; and financing
entities—including venture capital, public financing, angel financing and crowdsourcing.
Specifically, we explore how intermediaries operate in the context of scientific
entrepreneurship by providing a set of specialized services to advance the
commercialization of science. What unites these various intermediaries is their function
and provision of both complementary and related services in support of scientific
commercialization through entrepreneurship. After a brief framing of intermediation, we
review the literature on each organization type in turn, providing a definition and
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considering the contribution of the intermediary and the related policy implications. Each
section concludes with suggestions for additional research.
II.
Intermediaries Inside and Out
Consideration of intermediaries adds a new theoretical dimension to studies on the
commercialization of science. The Bush (1945) linear model argued that
commercialization could be left entirely to the private sector if government supported
upstream research (Hart, 1998). Stokes (1997) however questioned this division of labor
arguing that interactions between public and private sector actors are often essential for
bringing scientific discoveries to market. Adding to the discussion, Branscomb and
Auerswald (2002) used the colorful metaphor “valley of death” to not only explain a
frequent failure with science-based commercialization, but also to recognize the need for
intervention to bridge these noted gaps.
As this suggests, the ability to commercialize science depends on complex, dynamic
and adaptive responses and relationships among private, quasi-public and public sector
organizations. The concept of systems of innovation has been used to capture the
relational dimensions and characteristics of environments that support knowledge
creation and enhance innovation (Edquist, 1997). Systems of innovation are most
succinctly defined as “the set of institutions whose interactions determine the innovative
performance...of national firms,” (Nelson & Rosenberg, 1993: pp. 4-5). Yet the innovation
system approach often assumes homogeneity within a single country, when significant
regional differences within countries suggest that innovation is more often a subnational
phenomenon.
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Recent work by several European scholars has attempted to expand the Triple Helix
model to include intermediaries that operate between universities, industry and
government in several European contexts (Fernández-Esquinas et al., 2016; Suvinen et al.,
2010; Todeva, 2013). While this work attempts to make the role of intermediaries more
central, and uncovers the specific challenges of intermediation between the tripartite
partners with differing goals, the theory is limited by its singular focus on universityindustry-government links.
In contrast, the ecosystem concept, which originated with practitioners in the mid1990s (Autio & Thomas, 2014), recognizes the micro-geography of innovation and thus
captures the diverse mix of locally-embedded support organizations that contribute to
innovation. The modern concept of an innovation ecosystem is rooted in the earlier
literature on systems of innovation and builds upon endogenous growth theory (Romer,
1990). New Growth Theory puts knowledge creation at the center of models of economic
growth, while resonating with observations of the dynamic intra-regional social relations
described as part of late 19th century Marshallian industrial districts. Increased interest in
capturing the sub-national geography of innovation suggests an opportunity to look closely
at the intermediary organizations that contribute to the vital health of a regional
innovation ecosystem.
It has long been recognized that innovative firms must be able to access, acquire,
assimilate and exploit external knowledge to develop and sustain competitive advantage
(Cohen & Levinthal, 1990; Zahra & George, 2002). Yet firms, especially small
entrepreneurial firms, rarely innovate in isolation. Networking with other firms often aids
in the transmission of tacit and highly complex knowledge across firm boundaries, where
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vertical integration is inefficient and knowledge cannot be easily priced (Powell, 1990).
Equally important, however, is access to other mediating agents and intermediary
organizations that act as boundary spanners to help facilitate network formation among
firms, while also extending essential resources, services, and guidance in support of
innovation and the transfer of tacit and explicit knowledge (Howells, 2006; Wright et al.,
2008).
Intermediaries are especially important for science-based entrepreneurial firms
given high barriers to commercializing scientific knowledge. At a general level,
intermediary organizations support innovation by directly engaging with individual
establishments through the provision of services and access to resources that can enhance
business development or expedite technology commercialization. More specifically,
intermediaries work with science-based entrepreneurs to overcome information and
resource asymmetries by providing specialized information about: intellectual property
protection, the navigation of clinical trials in the life sciences, and the negotiation of
technical standards for firms innovating in information, internet, and equipment
technologies. Some intermediaries offer specialized services that help entrepreneurs refine
their ideas and business plans, reducing the transaction costs of engaging in
commercialization activity. McEvily and Zaheer (1999) find that the development of new
capabilities is stronger in firms with ties to regional intermediaries. Intermediaries can
also help firms resolve financial constraints either directly, through subsidies, or indirectly,
by making introductions to other sources of finance.
Intermediaries also play an essential coordinating role, forging networks and
partnerships across the science-based business community and introducing nascent
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entrepreneurs to more established and influential business leaders, mentors, or partners.
In this regard, intermediaries do not just address innovation gaps at the individual firm
level. They also contribute to agglomeration economies by shaping and reshaping
relational dynamics within and across the regional economy, through the creation of an
industry commons (Berger, 2013). Intermediaries diffuse knowledge across firms and
supply chains, thus providing a mechanism to give greater material substance to the
concept of knowledge spillovers. While Marshall notes that the “secrets of the industry are
in the air”, these intermediate support organizations provide channels for air circulation.
Corredoira and McDermott (2014) support these findings, suggesting that intermediaries
play an invaluable role in filling structural holes that separate firms, allowing for the fluid
movement of knowledge. Their geographic concentration can also contribute to greater
regional specialization, thereby helping to motivate new product and firm development
(Feldman & Kogler, 2010). It is important to consider the possibility of negative
externalities from the networking role of intermediaries. Pahnke et al. (2015) find evidence
of competitive information leakage across shared intermediaries. Specifically, when firms
are indirectly linked because they share the same intermediary (e.g., a VC firm),
information may accidentally be leaked to a competitor and hinder—rather than support—
innovation. This suggests that there are important qualitative differences in the ways that
intermediaries operate.
Innovation is clearly a high-risk undertaking, not simply for entrepreneurial firms
that seek to transform novel ideas into society-enhancing solutions and marketable
products, but also for the regions in which these innovative firms are embedded. In this
regard, it is important to also recognize a third, yet often obscured contribution of regional
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intermediaries. An intermediary can reach well beyond the business community to support
and sustain regional innovation and science commercialization through their on-going
interaction with other intermediaries. This is the essential idea behind innovation systems
or ecosystems: the whole is greater than the sum of the parts. Intermediaries have been
known to join forces in order to shape and inform policy action and regional strategy, even
engaging in forms of collective action to amass political support in order to advance policy
goals and capacity building (Feldman & Lowe, 2017). But equally, intermediaries align
efforts in order to shape the types of scientific discoveries that get commercialized by local
entrepreneurs, and in ways that often reflect the unique social, environmental or
technological challenges facing residents in their region (Owen-Smith & Powell, 2006). In
this respect, intermediaries are not only well-poised to address some of the emergent gaps
in U.S. federal science policy, but they also provide a resource for guiding policy in support
of science commercialization and regional economic development.
Table 1. Intermediary Definitions and Roles in Scientific Entrepreneurship Here
III.
Methodology
With this potential contribution in mind, we began this analysis with an examination
of the ecosystem literature. Admittedly the ecosystem concept encompasses a variety of
culture, social, and symbolic conditions that augment the contribution of more formal
support institutions (Stam, 2015). Still, as Spigel (2015) notes, formal institutions within an
ecosystem are tangible entities that are most easily influenced by policy. We focus on five
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tangible, physical entities most commonly featured in ecosystem analysis: university
technology licensing offices; professional service firms; workspace providers, including
incubators, accelerators, and coworking spaces; organizations that provide networking and
programmatic assistance; and financing entities, including venture capital, angel
investment, public funding, and crowdsourcing. Table 1 defines each intermediary and
provides examples of their role in scientific entrepreneurship.
For each of these categories, we conducted an extensive literature search using a
variety of keywords outlined in Appendix A. This produced a large cross-section of the
literature. Scholarly journal articles were found through online searches of bibliographic
databases such as: Web of Science, Google Scholar, and ProQuest Summon. In an effort to
reduce bias in the results of searches, we specifically included highly cited as well as more
recent articles. We also included articles from a range of journal rankings and disciplinary
fields. Papers were included based on whether they contributed to the state of knowledge
on intermediation or a specific intermediary organization.
IV.
University Technology Transfer and Licensing Offices
The commercialization of academic science typically begins with university
technology transfer or licensing offices (TTO) that work with businesses to license a
university-created technology (Spigel, 2015; Stam, 2015). In the U.S., the Bayh-Dole Act of
1980 formalized a process for the licensing of university inventions that resulted from
government-funded research, although there was an historical precedent for university
ownership (Mowery et al., 2004). Other countries have adopted policies similar to the U.S.
system of university ownership or—alternatively—assert professors’ privilege so that the
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individual inventor retains ownership (Cunningham & Link, 2016; Huyghe et al., 2016).
Many reviews consider the role of universities in the economy and highlight their role in
ecosystems (D’Este & Patel, 2007; Etzkowitz et al., 2000; Rothaermel et al., 2007). Our
focus, however, is limited to the specific role of TTOs as intermediary organizations that
assist in the commercialization of science. It is worth noting that ideas with scientific value
can also originate from government labs and from private firms, although there is less
research on their commercialization efforts. For private firms, internal offices and legal
counsel (rather than intermediaries) manage the licensing relationship (Kline, 2003; Maine,
2008).
Technology transfer offices participate in markets for technology, defined as
“transactions for the use, diffusion and creation of technology (or intellectual property),”
(Arora et al., 2001, pp. 423). While firms of all sizes license technology, academic startups
feature most prominently in scholarly work as they are seen to offer the possibility of
greatest impact. Yet university technology transfer is characterized by highly skewed
distributions, with the majority of offices failing to break even while other TTOs have big
hits and enjoy strong revenue flows (Feller and Feldman, 2010). Siegel and Wright
(2015a) argue that TTOs overcome three main challenges: first, they provide faculty
incentives to disclose inventions and engage in the commercialization process; second,
TTOs maintain researcher involvement in the development process, and; third, they
provide information about the value of technology. Of course, faculty can bypass the formal
TTO process by patenting directly with industry (Siegel et al., 2004). While some critics
complain that licensing may diminish the traditional strength of informal university
knowledge spillovers, Thursby and Thursby (2002) provide evidence that this is not the
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case. Wright et al. (2008) find, however, that TTOs better intermediate the transfer of
explicit rather than tacit knowledge in a study of TTOs in the U.K., Belgium, Germany, and
Sweden.
The organization of the TTO as well as the level of resources committed by the
university are important to the capacity to commercialize technology (Bercovitz et al.,
2001; Siegel et al., 2003). Thursby and Kemp (2002) found that private universities tend to
be more efficient in licensing than public universities, while universities with a medical
school are less efficient in licensing. O’Shea et al. (2005) found that the number of startups
a university is able to generate is related to: past university TTO success, faculty quality,
the size and source of research funding, and the amount of resources devoted to TTO staff.
Markman et al. (2005) find a positive relationship between the speed with which the TTO
processes new invention reports and the creation of startups. Importantly, based on the
case of Belgium’s K.U. Leuven TTO, Debackere and Veugelers (2005) argue that wellmanaged and structured TTOs reduce information asymmetries between industry and
university, fostering industry-university linkages that are lacking in the European context
and cause the “European paradox” of high levels of scientific expertise, with low
contributions to industry. The finding by Huyghe et al. (2016) that more than half of
surveyed pre- and postdoctoral researchers at 24 European universities were completely
unaware of their university’s tech transfer operations, however, is not an encouraging
figure.
TTOs use various mechanisms to improve the commercialization of academic
science, including equity and uniform startup licenses, to educational support programs,
and incubators. Universities started using equity in lieu of licensing fees to encourage new
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firm formation (Feldman et al., 2002). Di Gregorio and Shane (2003) found that TTO
policies, rather than capital market constraints, impact the number of new ventures
created: more startups are formed when TTOs make equity investments. Many types of
licensing agreements are used by TTOs, with new express licenses recently becoming
popular (Rector & Thursby, 2016).
The commercialization of academic science now involves more stakeholders,
especially at the regional level. Furthermore, the methods of commercialization have
expanded, e.g., accelerators and business plan competitions (Siegel & Wright, 2015b). If the
local TTO is not effectively engaged, other intermediaries are likely to gain importance in
the ecosystem. If TTOs serve an important purpose, then the faculty that commercialize on
their own (either through professor privilege or who choose to circumvent the process)
should find a substitute intermediary. And even when the university TTO is well resourced
and has a strong history, other intermediaries may assist commercialization activity.
V.
Physical Space: Incubators, Accelerators, and Coworking Spaces
The commercialization of science requires physical workspace, laboratory space,
clean rooms and advanced equipment. Incubators, accelerators, and coworking spaces
provide entrepreneurs access to physical facilities at below market rates, and with
preferential terms. Moreover, the co-location of physical facilities allows for the circulation
of ideas. Incubators, accelerators, and coworking spaces may be affiliated with universities
or alternatively operate as public, for-profit, or nonprofit entities. Mian et al. (2016) calls
for the development of a field of study called Technology Business Incubation (TBI) to
further define these intermediaries’ contributions. Perhaps what is most interesting is that
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while incubators have been in existence over half a century, accelerators are a much newer
phenomenon, and new organizational forms (such as coworking spaces) are proliferating.
In general, the trend is for physical space providers to add services that aid
commercialization, reflecting the political and social context surrounding these
organizations (Phan et al., 2005).
Incubators
Incubators, as the name implies, attempt to support early stage firms to a point
where they hatch or become viable entities. The expectation is that successfully incubated
firms can exit in a strategic business position (Aernoudt, 2004). Though first appearing in
the 1950s, incubators began to grow in number in the U.S. during the 1980s for reasons
including: the passing of Bayh-Dole, expansion of IP rights in the U.S., and newfound profits
from biotechnology commercialization—all factors driven by the potential for
commercializing science (Hackett & Dilts, 2004). The rise of European science parks
occurred largely as a result of Triple Helix partnerships designed to replicate U.S. successes
(Colombo & Delmastro, 2002).
Categorizing the organizational forms and management practices of incubators has
been a vexing problem and is one reason why there is little conclusive empirical research.
Bruneel et al. (2012) present an evolutionary process that characterizes generations of
incubators, with each augmenting the value proposition. First generation incubators
focused only on offering affordable space, while second generation incubators added
knowledge-based business support services. Third generation incubators began to add
networking support and serve earlier stage companies, focusing more on selection and
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quicker tenant turnover, in an effort to make profits. While the earliest incubators were
publicly financed, for-profit and corporate incubators emerged, with incumbent companies
offering incubation as a means to generate new sources of revenue (Becker & Gassman,
2006).
Incubators can also be categorized according to their objectives: mixed type
incubators serve all technologies and types of firms, while economic development
incubators aim to leverage local activities to create employment opportunities (Aernoudt,
2004). A third category, technology incubators, typically focus on specific sectors (often
aligned with cluster development strategies) and offer access to shared specialized
resources, such as testing facilities or chemical formularies that are especially important
for the commercialization of science. In a study of 13 specialized and 13 diversified German
business incubators, Schwartz and Hornych (2010) find a firm's industry rather than
incubator specialization better explains the likelihood of firm linkages to academic
institutions, and find no difference in internal network patterns between incubator types.
This heterogeneity of mission, organizational form and practice complicates impact
assessments (Mian, 1996, 1997; Di Gregorio & Shane, 2003; Bergek & Norman, 2008;
Hackett & Dilts, 2004, 2008; Mian et al., 2016; Theodorakopoulos et al., 2014).
Not surprisingly, the effectiveness of incubator participation on the
commercialization outcomes of individual firms also varies. Schwartz (2013) found
incubated firms do not have a statistically significantly higher chance of survival than nonincubated firms. In contrast, Lewis et al. (2011) used discriminant analysis and found
business incubation positively impacts firm outcomes. Incubator quality is more predictive
of outcomes than incubator size, age, or regional capacity for entrepreneurship. They also
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found most top-performing incubators tend to: be nonprofit, have government support,
have larger budgets, and exhibit similar management practices. Furthermore, incubator
success is correlated with having incubator graduates and technology transfer specialists
on the incubator’s board.
In interesting new research analyzing the roles of business incubators in emerging
markets, Dutt et al. (2016) find these incubators may operate as “open system
intermediaries” to support market development as well as to support individual business
development. These contrast to “closed system intermediaries,” as open system
intermediaries “seek to create benefits for parties beyond a well-identified set of
participating actors,” (pp. 819). More research on intermediaries in these emerging
economies is warranted.
The number of incubators is ever increasing, suggesting an opportunity for
evidence-based research to guide operations. Contradictory results may reflect the wide
range of services offered by incubators from subsidized real estate to intensively managed,
supportive environments. This suggests the possibility of developing a matrix of incubator
characteristics matched against the local characteristics of entrepreneurs and the existence
of other support organizations in the region.
Accelerators
Although accelerators have been described as a “new generation incubator model”
(Pauwels et al., 2015, pp. 13), they differ from incubators on a number of variables—
including: duration, business model, selection, and mentorship—among others (Cohen,
2013). Firms are typically provided with a small investment in return for an equity share.
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Selection into accelerators is highly competitive, which sends a quality signal to outside
investors (Kim & Wagman, 2014). Accelerators make extensive use of seminars for
education about entrepreneurship. Furthermore, mentorship is intense in accelerators and
a multitude of relationships can exist between the accelerator and the startup, including:
direct investment, help with finding additional investment, and partnering in pilot
production and distribution (Kohler, 2016). Accelerators also stress finding the value
proposition for the customer, which can be especially beneficial for scientists turned
entrepreneurs who tend to focus on the scientific aspects of their firm. Moreover, many
accelerators focus on ideas, projects or ventures before the formation of a company. After
an intense three to six-month program, entrepreneurs have gained information about the
viability of their project—the science may be strong, but if a market does not yet exist then
it is not a good opportunity.
Accelerator funders are more like venture capitalists in that they invest in a group of
firms, while only expecting to receive large returns on just a few ventures. Therefore, they
will accept earlier investments overall, which is important for commercializing science.
Hallen et al. (2014) study the impact of accelerators based on the time it takes ventures to
reach certain milestones, such as the first round of VC. They find mixed results using a Cox
proportional hazard model on a matched set comparison of accelerated and nonaccelerated ventures. They find no difference between accelerated and non-accelerated
firms, however firms in some specific accelerators did realize a faster time to milestones
than did other accelerators. Hallen et al. (2014) argue these results are indicative of the
difficulties in the acceleration process. Empirical work is needed to shed further light on
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acceleration processes and outcomes, as data on accelerators becomes more widely
available.
Recent studies find accelerators do have an effect on early firm outcomes. Smith
and Hannigan (2015) use hazard analysis to compare startup exits and follow-on funding
outcomes between accelerated and angel-funded firms. With data from two top
accelerators and 19 top angel funders, they find accelerated ventures are more likely to exit
by acquisition, and at an earlier date, than angel-funded firms. Accelerator firms are also
more likely to receive a first round of VC funding earlier than angel-funded firms, and this
earlier date is around the time of the accelerator’s ‘demo day’. Smith and Hannigan (2015)
argue these findings are the result of differences between the processes of angel versus
accelerator investing, and the ways in which angels and accelerator managers realize
returns. The fact that accelerator operators invest in cohorts and spend more time
nurturing and mentoring the firms could be such an explanation.
The presence of an accelerator may signal a strong or growing entrepreneurial
ecosystem. Fehder and Hochberg (2014) use difference-in-differences analysis to analyze
the impact of accelerators on entrepreneurial ecosystems. They find that startups located
in MSAs with an accelerator receive more financing whether or not they participated in the
accelerator, and argue this indicates that accelerators have an impact on ecosystem
strength. The role of accelerators in ecosystems and compared to other workspace
provision models, however, would benefit from greater theoretical and empirical
development.
Coworking Spaces
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Coworking spaces—a low rent, alternative workspace purported to offer a fun and
informal atmosphere—are another new phenomenon in the workspace intermediary field.
Coworking spaces are distinguished from earlier shared office facilities by their emphasis
on social interactions, aesthetic design and management by cashed out entrepreneurs and
potential investors (Waters-Lynch et al., 2016). They are found in hotspots of activity and
range from small operations to national organizations—such as WeWorks—and large
firms—such as Microsoft and Google. Incubators and accelerators have evolved to offer
coworking spaces, but Moriset (2014) questions their future, arguing the spaces neither
create much profit for operators, nor add much value to occupants.
There are three types of coworking space users: freelancers, microbusinesses, and
people working for themselves or for companies external to the space (Parrino, 2015).
Knowledge exchange through collaborative relationships only occurs when the coworking
organization encourages such collaboration—co-location alone does not foster
collaborative relationships. Data from an online coworking magazine, Deskmag, indicates
entrepreneurs are present and active users of coworking spaces; approximately, 20% of
coworkers are entrepreneurs that employ other workers (Foertsch, 2011).
Research on the contribution of coworking spaces to science entrepreneurship is
limited thus far. A case analysis in South Wales found that coworking spaces support
entrepreneurs and entrepreneurial activities through networking, peer mentoring, and
allowing easier access to forms of capital, among other things; but, this study has limited
generalizability (Fuzi et al., 2015). Waters-Lynch et al. (2016) argue Schumpeterian
economic theory is a useful theoretical lens through which coworking may be studied to
understand how it contributes to innovation. For scientists working on an idea, a third-
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place to go to meet with like-minded people may be an important first step. Future
empirical work will be important for this field.
VI.
Professional Service Providers
Professional service firms (PSF) aid in the commercialization of science by vetting
proposals for new companies and connecting founders to a wider pool of resources,
networks, and entrepreneurial support. These service professionals have access to
specialized knowledge, are usually embedded in an existing entrepreneurial community,
and can serve as network bridges for new entrepreneurs, thus helping reduce transaction
and search costs (Zhang & Li, 2010). Extending the entrepreneurial ecosystem concept,
Stam (2015) considers PSFs to be vital “feeders” into that system. Hayter (2016) found
service providers are especially important to academic entrepreneurs as they provide
information related to law and accounting, as well as services such as product testing that
might not be accessible to them through their established academic networks.
Professional service firms have not been studied widely in the management
literature (Empson et al., 2015). This reflects difficulty in identifying which ancillary firms
qualify as technology intermediaries. Von Nordenflycht (2010) presents a taxonomy based
on three defining features: knowledge intensity, low capital intensity, and high degree of
professionalization. Knowledge intensity, the high degree of knowledge specialization, is
the most important defining feature. The higher the degree of knowledge specialization,
the more important the service is to the entrepreneur.
The majority of studies focus on law firms. Gilson’s (1984) seminal work found that
Silicon Valley attorneys act as transaction cost engineers, reducing costs of engaging in
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commercialization. In a study of prospective entrepreneurs, Shane (2001) found local
attorneys provide initial advice on patent protections and scope affecting the decision to
start a company. Accountants and investment bankers provide a similar function reducing
the impact of information market failures on startups (Gilson, 1984). Suchman and Cahill
(1996) found Silicon Valley business attorneys further define local business norms and
integrate norms into the legal and business community. Suchman (2000) found Silicon
Valley attorneys function as business counselors, dealmakers, gatekeepers, proselytizers,
and matchmakers. As dealmakers, lawyers link startups to other firms, such as VC. As
gatekeepers, they selectively connect startups to other members of their networks. As
proselytizers, they use their influence to educate startups on business norms, further
solidifying norms. As matchmakers, attorneys sort and match clients and resources. These
roles shape the broader community. Cable (2014) argues this model of startup lawyering
has grown with the proliferation of entrepreneurship as an economic development
strategy. Originating in Silicon Valley, the practice has several distinctive features as
attorneys set contract standards and defer initial payments in lieu of equity, believing that
greater return will follow.
In an investigation of the spatial patterns of semiconductor firms that recently had
their initial public offering, Patton and Kenney (2005) found that legal counsel used by
entrepreneurs is always proximate to startup activity, followed by investment bankers,
venture capital, and finally independent directors. While locational patterns differ across
industries, a subsequent paper using the same data found that attorney startup services
remain highly local (Kenney & Patton, 2005).
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Gompers and Lerner (2010) argue real estate brokers and managers familiar with
equity investing also reduce transaction costs of obtaining finance. Accountants and
investment bankers provide a similar function reducing the impact of market failures on
startups (Gilson, 1984). Zhang and Li (2010) analyzed the impact of startup network ties to
PSFs on production innovation in a study of 202 firms in a Chinese technology cluster. They
found new ventures’ networks with technology service firms, law firms, and accounting
firms have a positive impact on firm product innovation.
The sparse and disconnected nature of the literature outlined here shows ample
room for continued research on the role of PSFs as intermediaries in the entrepreneurship
and technology commercialization process. The literature lacks a theoretically constructed
conceptualization of the impact of attorneys, accountants, insurance agents, and other
service providers, on technology commercialization. Additional analysis at a regional scale
will be most useful as previous studies show service providers mostly operate at a local
level. Finally, an important, yet unanswered, question raised by Friedman et al. (1989) is
whether Silicon Valley attorneys help the high technology industry grow, or whether—
conversely—the high technology industry led to growth in the local legal sector. Perhaps it
is less a case of determining directionality, and more a future research opportunity for
studying positive feedback and mutual reinforcement.
VII.
Networking, Connecting and Assisting Organizations
Public, quasi-public and nonprofit programs frequently step in to support scientific
entrepreneurship. These public service organizations have limited expectation for direct
financial gain, but rather a greater focus on the public outcomes of economic growth
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through the promotion of startups. They serve networking support roles for entrepreneurs,
coordinating local organizations and programs by bringing together public and private
entities, and serve agenda-setting roles for policy and practice. Motivated to serve a public
purpose, these organizations exist to address network failures (Schrank & Whitford, 2009).
One example of such an organization is the North Carolina Biotechnology Center
(herein, “the Biotech Center”), established by the North Carolina legislature in 1981 as a
nonprofit 501c3, with the majority of its budget derived from annual state appropriations
(Feldman & Lowe, 2011). As a quasi-public nonprofit, the Biotech Center has the option to
secure additional funding, including federal research grants. This nonprofit structure has
enabled the Biotech Center to position itself as less partisan, and thus retain state support
even during changing political environments (Lowe & Feldman, 2015). Another example of
a successful quasi-public, coordinating, and networking program is the San Diego
CONNECT program. This intermediary was founded in 1985 as a bottom-up effort of
entrepreneurs, supported by economic development officials, to connect industry to
academia and advance local entrepreneurship and the commercialization of academic
science (Kim & Jeong, 2014; Walcott, 2002). Disconnecting from the university may have
allowed CONNECT to reach a broader base of entrepreneurs to assist.
Not-for-profit organizations with more limited government involvement also offer a
portfolio of topical programs to respond to local needs and contribute to the
commercialization of science through entrepreneurship. One example is the nonprofit
Council for Entrepreneurial Development (CED), one of the nation’s first membership
organizations dedicated to new firm support by providing: networking assistance,
mentorship, entrepreneurial education and training, and identification of capital sources.
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Research finds such organizations efforts fruitful. Cumming and Fischer’s study (2012) of a
one-stop Innovation Synergy Center in Ontario, finds that publicly-provided business
advisory services positively affect entrepreneurial outcomes.
Both nonprofit and quasi-public programs can operate at multiple scales. Nonprofits
such as SCORE and America’s Small Business Development Centers (SBDC) have a national
reach and receive federal funding from the Small Business Administration (SBA), though
operate a decentralized network of local programs. SCORE offers entrepreneur training
workshops and mentoring through over 300 chapters. SBDC is an entrepreneur and small
business assistance network that offers training and mentoring through partnerships with
universities and state economic development agencies. Chrisman et al. (2005) found the
time entrepreneurs spent in “guided preparation” with an outside advisor at SBDCs prior to
starting a company was associated with increased startup performance, including better
employment and sales outcomes. Still, the time spent had diminishing marginal returns.
Yusuf (2010) argues that startup assistance programs like these may not have an
immediate effect, but often help support entrepreneurs’ latent, rather than perceived,
needs.
Local programs to support entrepreneurship also exist, which may be directed by a
higher level of government. In their case study of a Midwest region Feldman and Lanahan
(2010) find that firms pursue state and local funding programs more often than federal
programs. They also find local innovation programs have difficulty coordinating activities
and practices, and argue for the creation of bottom-up regional coordinating bodies.
As nonprofit and quasi-public structures and governing bodies continue to
proliferate, there is a need for greater research on these organizations, their programs and
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their impact. Multiple points of contact, however, make evaluations of single organizations
more difficult. There is an opportunity for more empirical work on the interaction,
sequencing and coordination of various forms of public and quasi-public support.
VIII.
Finance Providers
Finance organizations are especially important intermediaries for supporting the
commercialization of science through entrepreneurship. Without money, science and
technology-based companies simply cannot grow. Kerr and Nanda (2015) review the
literature on innovation finance and find that four features of the R&D process constrain
finance. First, the innovation process is uncertain. Second, innovation’s returns are highly
skewed. Third, information asymmetries between entrepreneurs and investors favor
entrepreneurs. Fourth, new innovation-focused ventures often rely on intangible assets
that can easily be lost if employees leave. The expenses for science based startups are
higher than average due to the costs of: labs and clean workspaces, highly skilled
employees, insurance, consulting services, and the need to protect intellectual property.
This list of expenses could easily be substantially increased, depending on the technology.
Thus, a variety of entrepreneurial funding sources have emerged to help companies
commercialize. These sources entail varying costs to the entrepreneur, and provide
different degrees of value-added services. For example, both banks and VCs monitor
investee firms, but VCs also offer value-adding services (Fraser et al., 2015).
Funding sources are typically characterized by ownership: public, nonprofit, and
private. Funding organizations may be local or operate at a national level. Furthermore,
universities take equity in academic startups in lieu of licensing fees, which provides
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legitimacy for the startup and allows the university to share in any potential upside
(Feldman et al., 2002). Entrepreneurs typically initially bootstrap their companies,
obtaining funding from what is known as the three F’s—friends, family, and fools. Other
financial intermediaries screen startups, provide contractual agreements, and monitor
investments on behalf of investors (Berger & Udell, 1998). We look at financial
intermediation in terms of its impact on commercialization outcomes, rather than just in
terms of financial outcomes for investors, and to investigate the nonpecuniary roles of
financial intermediaries.
Venture Capital
Defined as “the professional asset management activity that invests funds raised
from institutional investors, or wealthy individuals, into promising new ventures with a
high growth potential,” (Da Rin et al., 2012), VC firms operate as partnerships that raise
money from institutional and individual investors. They may be corporate, bank-owned,
private or government-sponsored. Private-sponsored VC is less common in European
countries than in the U.S. In Asian countries, however, VCs do not have the same
relationships with universities as in the U.S.: VC often invest in earlier stages in Asia than in
the U.S. (see Kenney et al. 2002 for a review of VC in Asia). VC funding is the most
extensively studied form of entrepreneurial finance and is noted to have an aggressive
management model that facilitates the commercialization of science. Samila and Sorenson
(2010, pp. 1358) argue, “venture capital supports the development of these [innovative]
ideas and helps to train and encourage a community of entrepreneurs capable of bringing
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those ideas to market,” making clear the contribution of VC as a commercialization
intermediary.
Venture capitalists use a multistage financing approach that provides funding in
tranches. This allows VC to stop funding if specific benchmarks are not met, or if it becomes
apparent that the firm is not going to succeed (Kerr, Nanda & Rhodes-Kropf, 2014). Public
research funding and VC are complementary and result in more innovative activity, as
measured by patents and startups, when a region has a greater amount of VC (Samila &
Sorenson, 2010). The ability of VC investment to stimulate innovation also depends on
characteristics of the VC firm (Kortum & Lerner, 2000). Hsu (2006) finds VC-funded firms
are more likely to engage in cooperative commercialization strategies such as strategic
alliances, and more likely to have an initial public offering (IPO) than non-VC funded firms.
These results were intensified when well known VCs provided funding. Hsu (2004) finds
that startups will pay more in terms of equity for investments from VC firms with higher
reputations. VC networks are useful to startups (Cable & Shane, 1997), yet Wright et al.
(2006) identify heterogeneity, as some VC have more social capital and involve themselves
more deeply with the company.
Cumming and Dai (2010) find VC investment decisions have a decidedly local focus.
Over 50% of investments are made in firms located within 250 miles of the VC firm’s office.
However, more reputable and well-networked VCs have a broader geographic reach. More
local bias is present when VC is specialized in a technology industry and when investments
are made in a greater number of rounds. Results show that local investments are more
likely to have successful exits, which also has implications for how VCs add value to
portfolio firms. Furthermore, the value-added effect of VC tends to vary depending on
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where the VC firm is located. Pinch and Sunley (2009), for example, find VC in the
Southampton, U.K. cluster are less effective as knowledge transfer agents than VC in
leading high-tech clusters such as Silicon Valley.
Cumming and Dai (2011) investigate the relation between VC fund size, and
successful firm exit—finding fund size has a diminishing marginal return to startups. In a
novel exploitation of exogenous variation in new airline routes, Bernstein et al. (2016)
found that greater on-site involvement, particularly of the lead VC, increased innovation in
firms along a number of dimensions; and interpreted these findings to indicate active
monitoring by VC is, in fact, a valuable asset for funded firms.
Wright et al. (2008, pp. 1209) argue, “venture capitalists and angels with specialist
technological skills may act as intermediaries that provide access to customers and
suppliers.” These connections may be especially important for technology based firms.
Vanacker et al. (2013) investigate how VC adds value to startups compared to angel
investors. They matched a sample of VC- and angel-backed firms to similar non-backed
firms and used OLS regression to assess impact on performance measured by gross profits,
finding both funding sources moderate the relationship between slack resources and firm
performance compared to non-backed companies. Angel investors are associated with
better use of human resources, while VC investment was associated with better financial
and human resource use. The results indicate that startups’ efficiency in operations, such as
commercialization, may benefit more from VC than angel investment. Furthermore, the VC
effect is correlated with the equity share—greater VC ownership increases performance.
The literature has also considered how VCs make investment decisions. Nanda and
Rhodes-Kropf (2013) found that hot markets make VC investors more willing to
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experiment by investing in more radical innovations. Bottazzi et al. (2016) find trust levels
affect VC decision-making and are a complement to contingent control contracts.
Specifically, higher trust predicts the likelihood of an investment being made, meaning
contracts are not used to overcome trust issues, but are used when trust exists.
Further investigation into the characteristics of VC, which allow them to best act as
local intermediaries and affect commercialization, would be useful. There is a need to
consider the match between VC characteristics and firm characteristics and
commercialization potential. Also, there is currently little research that considers how VC
interacts with other ecosystem intermediaries and members.
Angel Investors
Angel investors are individual investors who invest in smaller amounts and at an
earlier, riskier stage of startup development, which helps to provide proof of concept for
scientific discoveries. The total amount of startup financing provided by angels is greater
than the amount provided by VC (Wessner, 2002). Angels are often experienced
entrepreneurs with technology expertise, and offer advice and mentoring for an indefinite
amount of time (Cohen, 2013; Ibrahim, 2008). Beneficial for commercializing science,
angels also have much longer time horizons than VC as they do not have to exit at some
point on behalf of other investors, yet like VC they prefer to be located close to startups in
which they invest (Berger & Udell, 1998; Sohl, 1999).
Research on angel investment is still developing, constrained by a lack of data. Sohl
(1999, pp. 106) describes angel investment as a “relatively invisible” venture capital
market segment. Ibrahim (2008) observed a lack of interest by academics and media on
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this group, even as this group has attributes, such as patience and eclectic interests, that
make them good first investors in commercializing science. Ten years later this trend has
reversed, but the difficulty of obtaining data from private angel investors makes empirical
work challenging.
Studying this less visible group requires innovative techniques. Kerr et al. (2014)
used data obtained directly from organized angel groups in a regression discontinuity
design to study the effect of angels on firm outcomes. Defining a discontinuity threshold as
a level of critical interest shown in the company by angels, the results suggest that startups
funded by two successful angel groups had a higher probability of survival or successful
exit, and better employment outcomes than those rejected by the same groups. Bernstein et
al. (2015) performed a randomized field experiment using the online “AngelList” investing
platform to investigate how angel investors make investment decisions based on startup
characteristics. The manipulation of emails alerting investors of new investment
opportunities introduced exogenous variation into the information provided to potential
investors, allowing identification of angels’ interest level. Interestingly, angel investors
were more influenced by founding team composition than firm sales and the identities of
other investors, reinforcing the idea that this class of investor may be important for
commercializing science.
Public Funding
Public and quasi-public funding programs often extend financial support for
commercializing science. Government has taken an active role in supporting science and
innovation for over half a century, though direct public support for entrepreneurship is
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more recent. Public programs such as the U.S. Small Business Innovation Research (SBIR)
program, which provides highly competitive grants to develop technology for Federal
Agencies, have operated since the 1980s. Such programs operate outside the U.S. as well.
Aernoudt (2005) uses the case of a successful Belgian program to argue public coinvestment programs are an effective means to help angels spread risk.
A long literature evaluates the impact of the SBIR program (Lanahan & Feldman,
2015, 2017; Lanahan, 2016; Lerner 1999; Link & Scott, 2010; Qian & Haynes, 2014), yet
consensus on the program’s impact is elusive. An SBIR funded project faces a 50%
probability of failing to produce a commercialized technology, though Link and Scott
(2010) compellingly argue this an acceptable risk level for the federal government.
Reinforcing this, Lerner (1999) found that firms with SBIR grants grew faster in sales and
employment, and were more likely to receive subsequent VC investment than a matched
set of firms without SBIR; results were stronger in high-technology industries and in
regions with a higher concentration of VC. Furthermore, SBIR funding has a positive impact
on patenting levels in small and medium sized nanotechnology firms (Kay et al., 2013).
While U.S. states create their own entrepreneurship programs, they also leverage
and augment national programs. Forty-two states have SBIR service assistance programs
and 17 states have an SBIR matching grant (Lanahan & Feldman, 2015). Lanahan and
Feldman (2017) provide evidence of the efficacy of such policies, finding that firms that
receive an SBIR Phase I state match grant have a higher probability of receiving an SBIR
Phase II grant, when awarded from the National Science Foundation.
Finance is also available in the form of public VC. Pergelova and Angulo-Ruiz (2015)
analyze the impact of U.S. government equity, loan and guarantee programs for
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entrepreneurship, finding that guarantees and equity have a positive impact on firms’
competitive advantage and an indirect effect on profits. Public sources may offer less
added-value to startups engaging in commercialization than private sources, though.
Pierrakis and Saridakis (2017) find that U.K. firms receiving only public VC apply for less
patents than those obtaining only private VC, attributing this divergence to public fund
manager’s lack of expertise compared to private managers.
Indirect public efforts are also seen through attempts to stimulate investments from
private sources. Lerner (2002) argues government intervention, in the form of public VC, is
justified when public investment can certify firm quality to other investors, and when
technological spillover is possible. Several states have created investment programs, such
as Connecticut Innovations, a quasi-public, state-funded venture capital fund founded in
1989 (Feldman & Kelley, 2002). Lerner (2002) warns, however that public VC programs
can be inefficient and difficult to design.
It is certainly true that many public financing programs are oriented towards
capturing the benefits of science commercialization within their jurisdictions’ boundaries.
Moreover, different levels of governments, national and local, have the capacity to design
their own programs and experiment with different requirements and stipulations, which
makes program evaluation difficult. Future research should continue to investigate the
role public funding sources play in stimulating innovation and commercialization.
Crowdfunding
Crowdfunding is the newest—and least understood—practice in entrepreneurial
finance, and is defined as: “the efforts by entrepreneurial individuals and groups – cultural,
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social, and for-profit – to fund their ventures by drawing on relatively small contributions
from a relatively large number of individuals using the Internet, without standard financial
intermediaries" (Mollick, 2014, pp. 2). Crowdfunding emerged after the 2008 recession—
when bank finance became less available—and has become more structured with time,
though equity crowdfunding standards are slow to develop in many countries (Bruton et al.,
2015; Harrison, 2013). The 2012 JOBS Act legalized equity crowdfunding in the U.S.
(Agrawal et al., 2014).
Crowdfunding platforms allow individual or pooled investments in firms or projects,
usually called campaigns (Bruton et al., 2015). The use of web-based platforms offers an
opportunity to describe the science underlying a project and to reach a larger set of
potential investors than possible through the angel funding model. Crowdfunding models
also differ in how funders receive compensation. Donation models do not provide
compensation for investors and usually benefit nonprofits or charities. Reward models
offer gifts in return for investment. Pre-purchase models provide investors with the
product in which they invested. In lending models, investors receive returns following
typical borrow-lender relationships. Finally, equity models offer shares in profit, or
ownership (Harrison, 2013).
Current crowdfunding research is dominated by descriptive and case-based studies.
Lehner et al. (2015) uncover broad, nonfinancial implications of crowdfunding using four
campaign case studies, including crowdfunding’s ability to serve as an alternative
distribution channel where funders act as pre-market testers and help with problem
identification, quickening commercialization time.
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Several crowdfunding studies use data from Kickstarter, a prominent reward-based
platform. Frydrych et al. (2014) find certain signals impact how projects gain legitimacy,
including founding team composition and the time to achieving funding goals. Stanko and
Henard (2016) study innovation outcomes of successful Kickstarter campaigns and find
that beyond funds generated, campaigns help creators with product feedback and idea
sharing—important to commercialization. With surveys and data from over 200
Kickstarter firms they find the amount of subsequent innovation by campaigners is related
to campaign features, such as how open the campaign is to external ideas, and how early in
the development process the campaign began. These findings suggest that crowdfunding
may provide an enhanced commercialization model.
The geography of crowdfunding investment is of interest since its online basis
should theoretically obviate geographic bias. Agrawal et al. (2011) find geography does not
play a role in investment decisions once campaigners’ friends and family network is
controlled for in estimation. Still, most campaigns are concentrated in geographic regions
typically viewed as more entrepreneurial (Mollick, 2014), highlighting the need to consider
crowdfunding as part of the regional innovation ecosystem.
Though some entrepreneurial finance providers have been studied extensively,
there is a need to understand the relationships and dependencies among finance sources.
Learning how various sources impact the likelihood of receiving funding from different
sources will provide important information to entrepreneurs seeking to commercialize
scientific discoveries, and policy makers designing public finance programs. Better data is
imperative to extending research on angel investing and crowdfunding.
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IX.
Institutional Travels
Popular accounts of innovation in regional economies often presume venture capital
is the most essential institutional actor for supporting local entrepreneurship. But as
Lerner (2009) notes in The Boulevard of Broken Dreams, the presence of VC is not sufficient
to create an innovative local economy, and VC investment does not guarantee
entrepreneurial firms will be successful. As this comprehensive survey illustrates, there are
many other institutional actors in the mix, each adding additional and complementary
services and supports. In some cases, these intermediaries focus on a particular segment of
the local entrepreneurial community—the most focused of which are incubators,
accelerators and coworking spaces, which only service those firms that secure residency in
their facility. But others have a broader reach.
University TTOs are on the front lines of technology intermediation. The ability of
TTOs to accumulate stocks of human, network, and technological capital make them
important players in ecosystems. However, not much is known about their actual potential
for economic development and how policymakers might exploit their resources for broader
goals. While the TTO literature is expansive, there are gaps in our understanding of the
effectiveness and relationships of TTOs to other intermediaries in the ecosystem.
Incubators, accelerators, and coworking spaces offer firms and entrepreneurs
varying levels of support with one common feature—the provision of laboratory and/or
workspace. While incubators have been studied the most closely of all three types, there is
a need for more knowledge about incubation processes and effectiveness. The research on
accelerators and coworking spaces is much newer. Empirical and theoretical work is
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necessary to better understand how these organizations contribute to technology
commercialization and startup outcomes.
Another promising topic for future empirical research is professional services firms.
Though these firms are not as glamourized as accelerators and VC, for example, they
provide critical services that contribute to successful commercialization. The law literature
has extensively studied Silicon Valley attorneys, but without an empirical lens. Other
service providers are mentioned in studies, but often fail to receive due attention. The
innovation literature has studied PSFs in more depth than management, but this trend is
improving.
Additional research is needed to understand the networking function of institutional
intermediaries. Quasi-public programs are well positioned here, often connecting firms to a
broader range of private and public stakeholders compared to their counterparts in
academia or corporate settings.
Entrepreneurial finance has received the most attention, with decades of research.
Yet there is continuous innovation, including emergent funding models such as
crowdfunding, as well as the evolution of earlier finance sources making the area ripe for
continued inquiry. While the VC literature is extensive, literature investigating the
relationship between VC and other funding sources is less developed. The impact of
crowdfunders and angels on innovation is still unclear. Though at first glance
crowdfunding may appear to have less value-added services than angels and VC, recent
studies illuminate a number of features, like idea sharing and consumer feedback, which
angels and VC may not provide.
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In many ways, the journey from research funding to technology commercialization
via an entrepreneurial firm conjures up the image of an old suitcase or steamer truck
papered with all the tags from the destinations on its journey. Every single intermediary or
support organization that has contact with a firm leaves a fading, yet indelible mark.
Studying each institutional category in detail allows researchers to not only identify
important sources of divergence, but also begin to explore the interdependencies and
intersections of different programs. As we note, university TTOs have long been known to
partner with incubators and support organizations within their region. Reinforcing this,
Fini et al. (2011) recognize that university supports for academic spin-offs can act to
reinforce the contribution of other local support mechanisms.
In our own research, we introduce the concept of entrepreneurial pathways in order
to capture the different combinations and sequences of institutional supports that firms
engaged with over time to grow their business and support innovation (Lowe & Feldman,
2017). More than a static inventory, the pathway concept places the firm within a well
mapped institutional surrounding. It allows us to study the exact navigational routes that
firms use to traverse that regional institutional landscape, and thus offers a unique vantage
point for exploring the contribution of multiple institutions in advancing science,
innovation, and sustained entrepreneurial growth. As we begin to recognize this fuller
institutional picture of a region, it also creates an opportunity to propose an alternative
policy narrative—one less focused on evaluating and identifying the best institutional fix
and fit, and channeling all resources there—to one that instead considers the longer term
entrepreneurial value of having institutional diversity, even redundancy, within a regional
ecosystem.
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Paige Clayton (clayton3@live.unc.edu) is a doctoral student in the Department of Public
Policy at the University of North Carolina at Chapel Hill, where she received the 2014
Nancy W. Stegman Fellowship in Public Policy. Her research focuses on the areas of
innovation, entrepreneurship, economic development, and science and technology policy.
Maryann Feldman (maryann.feldman@unc.edu) is the Heninger Distinguished Professor in
the University of North Carolina Chapel Hill’s Public Policy Department, and a Research
Director at UNC Kenan Institute of Private Enterprise. Feldman’s research focuses on the
areas of innovation, commercialization of academic research, and factors that promote
technological change and economic growth.
Nichola Lowe (nlowe@email.unc.edu) is an Associate Professor in City and Regional
Planning at UNC-Chapel Hill. Lowe’s work focuses on the institutional arrangements that
lead to more inclusive forms of economic development and specifically, the role that
practitioners can play in aligning growth and equity goals.
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APPENDIX A
Literature search keyword combinations:
(1) intermedia* AND (technology commercialization OR academic entrepreneurship) AND
spin-off AND (local OR region)
(a) intermedia* AND spin-off AND (technology commercialization OR academic
entrepreneurship)
(2) ((intermedia* AND spin-off) OR (commercial* OR tech* transfer OR entrepreneur*))
AND university technology transfer/licensing office AND (local OR region)
(a) intermedia* AND spin-off AND university technology transfer/licensing office
(3) ((intermedia* AND spin-off) OR (commercial* OR tech* transfer OR entrepreneur*))
AND (KIBS OR professional service firm) AND (local OR region)
(a) intermedia* AND (entrepreneur* OR spin-off) AND (KIBS OR professional
service firm)
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(4) ((intermedia* AND spin-off) OR (commercial* OR tech* transfer OR entrepreneur*))
AND (government support program OR nonprofit support program) AND (local OR region)
(a) intermedia* AND (entrepreneur* OR spin-off) AND (government support
program OR nonprofit support program)
(5) ((intermedia* AND spin-off) OR (commercial* OR tech* transfer OR entrepreneur*))
AND (incubator OR accelerator OR coworking space) AND (local OR region)
(a) intermedia* AND spin-off AND (incubator OR accelerator OR coworking space)
(6) ((intermedia* AND spin-off) OR (commercial* OR tech* transfer OR entrepreneur*))
AND (venture capital OR angel OR crowdfunding OR public funding OR government
funding) AND (local OR region)
(a) intermedia* AND spin-off AND (venture capital OR angel OR crowdfunding OR
public funding OR government funding)
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Table 1. Intermediary Definitions and Roles in Scientific Entrepreneurship
Intermediary Type
Definition
Primary Roles in Scientific Entrepreneurship
Service Intermediaries
Provide incentives for invention disclosure
University Technology
University offices that manages intellectual property of
Transfer/ Licensing Offices
university-created technologies.
Engage faculty in development process
Work with businesses to license technology
Reduce transaction costs
Third-party firms—including law, accounting and real
Professional Service Firms
Advise IP and business formation strategy
estate firms—that provide resources and connections.
Act as dealmakers
Other Assisting
Public, quasi-public and nonprofits that provide
Facilitate networking and mentoring
Organizations
networking, specialized services and programs.
Influence policy through agenda setting
Physical Space Intermediaries
Offer affordable space
A physical space for early stage firm formation and idea
Incubators
Provide support services
development.
Generate revenue for incumbent firms
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Accelerators
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A physical space, complemented with provision of
Offer intensive programming
resources and financial investment.
Accelerate milestones
Invest in exchange for equity
Provide flexible, less structured programming
A physical space that promotes proximity and
Coworking Spaces
Offer space for social interaction
interaction.
Facilitate networking and peer mentoring
Financial Intermediaries
Investment firms that raise funds from individuals and
Provide multistage, benchmarked financing
Venture Capital Firms
institutions to support new ventures with high growth
Motivated to increase firm performance
potential.
Provide early stage funding
Individual investors or investment clubs that provide
Angel Investors
Source of patient capital
early-stage financing in support of new ventures.
Offer business advice and mentoring
Long term source of support
Public and quasi-public programs that provide financial
Public Funding Programs
Non-dilutive source of funding
assistance in the form of grants or loans to new ventures.
Signal quality for private financing mechanisms
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Recession proof
Funding platform to secure large numbers of small
Crowdfunding Platforms
Enable inventors to gain immediate product feedback
investments.
Support idea sharing
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